Currently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of the study is the generated data sets obtained on the basis of theoretical stress relaxation curves. Tables of initial data for training models for all samples are presented, a statistical analysis of the characteristics of the initial data sets is carried out. The total number of numerical experiments for all samples was 346020 variations. When developing the models, CatBoost artificial intelligence methods were used, regularization methods (Weight Decay, Decoupled Weight Decay Regularization, Augmentation) were used to improve the accuracy of the model, and the Z-Score method was used to normalize the data. As a result of the study, intelligent models were developed to determine the rheological parameters of polymers included in the generalized non-linear Maxwell-Gurevich equation (initial relaxation viscosity, velocity modulus) using generated data sets for the EDT-10 epoxy binder as an example. Based on the results of testing the models, the quality of the models was assessed, graphs of forecasts for trainees and test samples, graphs of forecast errors were plotted. Intelligent models are based on the CatBoost algorithm and implemented in the Jupyter Notebook environment in Python. The constructed models have passed the quality assessment according to the following metrics: MAE, MSE, RMSE, MAPE. The maximum value of model error predictions was 0.86 for the MAPE metric, and the minimum value of model error predictions was 0.001 for the MSE metric. Model performance estimates obtained during testing are valid.
With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect
... Show MoreUltimate oil recovery and displacement efficiency at the pore-scale are controlled by the rock wettability thus there is a growing interest in the wetting behaviour of reservoir rocks as production from fractured oil-wet or mixed-wet limestone formations have remained a key challenge. Conventional waterflooding methods are inefficient in such formation due to poor spontaneous imbibition of water into the oil-wet rock capillaries. However, altering the wettability to water-wet could yield recovery of significant amounts of additional oil thus this study investigates the influence of nanoparticles on wettability alteration. The efficiency of various formulated zirconium-oxide (ZrO2) based nanofluids at different nanoparticle concentrations (0
... Show MoreMicroalgae have been increasingly used for wastewater treatment due to their capacity to assimilate nutrients. Samples of wastewater were taken from the Erbil wastewater channel near Dhahibha village in northern Iraq. The microalga Coelastrella sp. was used in three doses (0.2, 1, and 2g. l-1) in this experiment for 21 days, samples were periodically (every 3 days) analyzed for physicochemical parameters such as pH, EC, Phosphate, Nitrate, and BOD5, in addition to, Chlorophyll a concentration. Results showed that the highest dose 2g.l-1 was the most effective dose for removing nutrients, confirmed by significant differences (p≤0.05) between all doses. The highest removal percentage was
... Show MoreComputer vision seeks to mimic the human visual system and plays an essential role in artificial intelligence. It is based on different signal reprocessing techniques; therefore, developing efficient techniques becomes essential to achieving fast and reliable processing. Various signal preprocessing operations have been used for computer vision, including smoothing techniques, signal analyzing, resizing, sharpening, and enhancement, to reduce reluctant falsifications, segmentation, and image feature improvement. For example, to reduce the noise in a disturbed signal, smoothing kernels can be effectively used. This is achievedby convolving the distributed signal with smoothing kernels. In addition, orthogonal moments (OMs) are a cruc
... Show MoreNumeral recognition is considered an essential preliminary step for optical character recognition, document understanding, and others. Although several handwritten numeral recognition algorithms have been proposed so far, achieving adequate recognition accuracy and execution time remain challenging to date. In particular, recognition accuracy depends on the features extraction mechanism. As such, a fast and robust numeral recognition method is essential, which meets the desired accuracy by extracting the features efficiently while maintaining fast implementation time. Furthermore, to date most of the existing studies are focused on evaluating their methods based on clean environments, thus limiting understanding of their potential a
... Show MoreImage steganography is undoubtedly significant in the field of secure multimedia communication. The undetectability and high payload capacity are two of the important characteristics of any form of steganography. In this paper, the level of image security is improved by combining the steganography and cryptography techniques in order to produce the secured image. The proposed method depends on using LSBs as an indicator for hiding encrypted bits in dual tree complex wavelet coefficient DT-CWT. The cover image is divided into non overlapping blocks of size (3*3). After that, a Key is produced by extracting the center pixel (pc) from each block to encrypt each character in the secret text. The cover image is converted using DT-CWT, then the p
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The work of this paper is an investigation to improve the condenser performance of the automobile air conditioning system by enhancing the air-side heat transfer from the condenser through the use of an air guide net installed in front of the condenser face which is basically an aluminum plate having a circular entrance shape for the air passage. The A/C system was examined under two types of test. The first test was conducted the air guide net, while the second was done with the air guide net. The performances of the A/C system under these tests were compared. For the second type of test, the experiment was carried out with three different size of air guide net, three different circular diameters (2, 3 and 3.5 cm) a
... Show MoreRoller compacted concrete (RCC) is a special type of concrete with zero or even negative slump consistency. In this work, it had aimed to produce an RCC mix suitable for roads paving with minimum cost and better engineering properties so, different RCC mixes had prepared i.e. (M1, M2, M3, and M4) using specified percentages of micro natural silica sand powder (SSP) as partial replacement of (0%, 5%, 10%, and 20%) by weight of sulfate resistant Portland cement. Additionally, M-sand, crushed stone, filler, and water had been used. The results had obtained after 28 days of water curing. The control mix (M1) had satisfied the required
In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and
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